How AI Is Transforming IoT Development in 2025 | 5 Real-World Applications

AI and IoT are two of the most transformative technologies in today’s business landscape, offering significant opportunities for innovation and competitive advantage. This article provides a brief overview of how the convergence of AI and IoT can transform business, and it also offers five real-world applications.

What is AIoT?

The Artificial Intelligence of Things (AIoT) is the convergence of artificial intelligence and the Internet of Things infrastructure. This integration creates smart, connected systems capable of collecting data from IoT devices and using AI to analyze that data—enabling intelligent decision-making without human intervention. IoT connects physical devices—such as sensors, machines, or wearables—to collect and exchange real-time data, while AI processes data to identify patterns, make predictions, optimize operations, and automate responses.

A key advance in modern AIoT solutions involves edge computing, which brings data processing to local devices rather than distant servers. This reduces latency for critical applications such as autonomous vehicles or medical monitoring while also enhancing security.

Below is a brief step-by-step explanation of how AIoT works.

Step 1: Data Collection: IoT devices gather real-time data from sensors—ranging from temperature sensors in factories to wearable health monitors.
Step 2: Data Transmission: The collected data is sent to cloud servers or processed locally on edge devices.
Step 3: Intelligent Analysis: AI algorithms analyze incoming data to detect anomalies, predict outcomes (such as equipment failure), or to personalize experiences.
Step 4: Autonomous Action: Based on insights generated by AI, systems can automatically trigger actions. For example, the system can automatically:

• Adjust building energy usage;
• Send maintenance alerts before breakdowns;
• Optimize supply chains in response to demand shifts.

Five Examples of Real-World AIoT Applications

In practical terms, AIoT applications range from predictive maintenance in industrial settings to intelligent traffic control in smart cities, enabling systems to respond dynamically to real-time data. By combining smart sensors with AI algorithms, organizations can automate decision-making, optimize operations, and enhance accuracy across complex environments. The following 5 real-world success stories demonstrate how AIoT is being applied to solve industry-specific challenges and drive digital transformation through intelligent, connected systems.

AIoT in Smart Manufacturing

Sheriff Tea Egg is a renowned Taiwanese food brand celebrated for its artisanal tea egg production. To meet rising quality standards and to scale operations, the company partnered with ASUS IoT and PH Precision to implement an AI-powered vision-inspection system that enhances defect detection, streamlines quality control, and integrates seamlessly with existing production-line equipment.

An advanced solution powered by a fanless ASUS IoT PE4000G industrial computer and AISVision software was deployed to provide robust computational efficiency and hygienic, dust-free operation—ideal for food manufacturing environments. As a result, Sheriff Tea Egg increased its yield rate from 93% to over 97%, reduced its dependence on manual inspections, and set a new benchmark for smart manufacturing in the local food industry.

AIoT for Recycling Systems

Textile recycling presents unique challenges due to the wide variety of fiber blends in consumer goods. Traditional systems often fail to accurately identify mixed fabrics, resulting in inefficiencies and excess waste.

ASUS IoT addressed this issue by deploying an advanced vision-based sorting system powered by deep learning and Convolutional Neural Networks (CNNs), enabling precise recognition of fiber types such as cotton, polyester, wool, and polycotton. The solution is driven by a suite of industrial edge devices, including the rugged, fanless PE3000G for real-time vision processing, the high-performance PE8000G for advanced sorting tasks such as foreign object detection and complex material classification, and the compact PE2100U for precise control of conveyor systems and sorting mechanisms. Together, these systems dramatically improve sorting accuracy, enhance throughput, and reduce dependence on manual sorting. The new system’s scalable, on-site architecture allows for real-time decision-making with minimal reliance on cloud infrastructure, helping the recycling sector meet sustainability goals, lower operational costs, and comply with increasingly strict environmental regulations.

AIoT in Smart City and Transportation

In the transportation sector, AIoT is revolutionizing urban mobility through smart parking systems that reduce congestion, improve user convenience, and cut environmental impact. A prime example is the collaboration between EPS Global and ASUS IoT, which delivers a scalable, intelligent parking management solution now deployed in cities across China, Europe, and the Middle East. EPS’s CityZen platform integrates real-time data from cameras and sensors to guide drivers to available parking spots, enable pre-booking, and streamline payments via mobile app. At the heart of the system, ASUS IoT provides robust edge computing hardware—including the Tinker Edge R for real-time data processing and display, the ALPR Edge AI platform for automatic license plate recognition, and industrial components that support secure, low-latency operations across diverse infrastructures. By combining EPS’s software expertise with the reliability of ASUS hardware, this AIoT-powered solution improves traffic flow, reduces emissions (from circling vehicles), and delivers a smoother, more sustainable parking experience.

AIoT in Smart Retail

In the retail sector, AIoT is unlocking powerful new ways to enhance customer engagement and operational efficiency through real-time data and intelligent automation. A strong example is the collaboration between meldCX^® and ASUS IoT, which powers the Viana™ vision analytics platform—an AI-driven solution designed to optimize in-store experiences. Using anonymized vision data and edge inference, Viana delivers actionable insights on audience behavior, ad performance, and customer interaction with digital signage. In support, ASUS NUC edge devices provide the necessary compute performance, flexibility, and scalability for rapid deployment of the solution across various retail environments. From personalized advertising to dynamic content triggering, the solution enables retailers to boost conversion rates and better understand shopper preferences. In one instance, Viana helped a retail media network more than triple advertising revenue within a month. With deployments expanding across shopping malls globally, meldCX^® and ASUS IoT are redefining how brick-and-mortar retailers compete in an increasingly digital-first world.

AIoT in Smart Agriculture

ASUS IoT collaborated with a French fruit producer to create a system for deploying autonomous mobile robots (AMRs) in agriculture. To overcome unique challenges—e.g., harsh outdoor conditions, limited network connectivity, and the need for precision—ASUS leveraged the ASUS IoT PE3000G, a fanless industrial PC equipped with a 12th Gen Intel^® Core™ i7 processor, and an Intel^® Arc™ MXM GPU. This solution facilitated advanced machine vision and AI inference directly on the robot, enabling it to navigate complex orchards, accurately identify ripe fruit, and operate reliably in extreme temperatures and rough terrain. The solution was transformative, boosting productivity and reducing headcount.

Learn More About ASUS and AIoT

AIoT solutions offer immense potential across diverse sectors. For more information about ASUS AIoT products and services, visit ASUS IoT. Or, contact us with specific questions about a solution for your business or organization.